Association of dietary patterns with obesity and metabolically healthy obesity phenotype in Chinese population: a cross-sectional analysis of China Multi-Ethnic Cohort Study

2022 ◽  
pp. 1-29
Author(s):  
Dan Tang ◽  
Xiong Xiao ◽  
Liling Chen ◽  
Yixi kangzhu ◽  
Wei Deng ◽  
...  

Abstract Metabolically healthy obesity (MHO) might be an alternative valuable target in obesity treatment. We aimed to assess whether alternative Mediterranean (aMED) diet and Dietary Approaches to Stop Hypertension (DASH) diet were favorably associated with obesity and MHO phenotype in a Chinese Multi-Ethnic population. We conducted this cross-sectional analysis using the baseline data of the China Multi-Ethnic Cohort (CMEC) study that enrolled 99 556 participants from seven diverse ethnic groups. Participants with self-reported cardiometabolic diseases were excluded to eliminate possible reverse causality. Marginal structural logistic models were used to estimate the associations, with confounders determined by directed acyclic graph (DAG). Among 65 699 included participants, 11.2% were with obesity. MHO phenotype was present in 5.7% of total population and 52.7% of population with obesity. Compared with the lowest quintile, the highest quintile of DASH diet score had 23% decreased odds of obesity (OR = 0.77, 95% CI: 0.71-0.83, Ptrend <0.001), and 27% increased odds of MHO (OR = 1.27, 95% CI: 1.10-1.48, Ptrend =0.001) in population with obesity. However, aMED diet showed no obvious favorable associations. Further adjusting for BMI did not change the associations between diet scores and MHO. Results were robust to various sensitivity analyses. In conclusion, DASH diet rather than aMED diet is associated with reduced risk of obesity and presents BMI-independent metabolic benefits in this large population-based study. Recommendation for adhering to DASH diet may benefit the prevention of obesity and related metabolic disorders in Chinese population.

Diagnosis ◽  
2014 ◽  
Vol 1 (2) ◽  
pp. 155-166 ◽  
Author(s):  
David E. Newman-Toker ◽  
Ernest Moy ◽  
Ernest Valente ◽  
Rosanna Coffey ◽  
Anika L. Hines

AbstractSome cerebrovascular events are not diagnosed promptly, potentially resulting in death or disability from missed treatments. We sought to estimate the frequency of missed stroke and examine associations with patient, emergency department (ED), and hospital characteristics.Cross-sectional analysis using linked inpatient discharge and ED visit records from the 2009 Healthcare Cost and Utilization Project State Inpatient Databases and 2008–2009 State ED Databases across nine US states. We identified adult patients admitted for stroke with a treat-and-release ED visit in the prior 30 days, considering those given a non-cerebrovascular diagnosis as probable (benign headache or dizziness diagnosis) or potential (any other diagnosis) missed strokes.There were 23,809 potential and 2243 probable missed strokes representing 12.7% and 1.2% of stroke admissions, respectively. Missed hemorrhages (n=406) were linked to headache while missed ischemic strokes (n=1435) and transient ischemic attacks (n=402) were linked to headache or dizziness. Odds of a probable misdiagnosis were lower among men (OR 0.75), older individuals (18–44 years [base]; 45–64:OR 0.43; 65–74:OR 0.28; ≥75:OR 0.19), and Medicare (OR 0.66) or Medicaid (OR 0.70) recipients compared to privately insured patients. Odds were higher among Blacks (OR 1.18), Asian/Pacific Islanders (OR 1.29), and Hispanics (OR 1.30). Odds were higher in non-teaching hospitals (OR 1.45) and low-volume hospitals (OR 1.57).We estimate 15,000–165,000 misdiagnosed cerebrovascular events annually in US EDs, disproportionately presenting with headache or dizziness. Physicians evaluating these symptoms should be particularly attuned to the possibility of stroke in younger, female, and non-White patients.


2019 ◽  
Vol 19 (1) ◽  
Author(s):  
Jean-David Zeitoun ◽  
Matthieu Faron ◽  
Sophie de Vaugrigneuse ◽  
Jérémie H. Lefèvre

Abstract Background It has been suggested that poor health has influenced vote for Brexit and the US presidential election. No such research has been published regarding the 2017 French presidential election. Methods We performed a cross-sectional analysis using a comprehensive set of socioeconomic and health indicators, to be compared with voting outcome at the first round of the 2017 French presidential election. The 95 French departments were selected as the unit of analysis. Data were obtained from publicly available sources. The linear model was used for both univariate and multivariate analysis to investigate the relation between voting patterns and predictors. Sensitivity analyses were done using the elastic-net regularisation. Results Emmanuel Macron and Marine Le Pen arrived ahead. When projected on the first factorial plane (~ 60% of the total inertia), Emmanuel Macron and Marine Le Pen tended to be in opposite directions regarding both socioeconomic and health factors. In the respective multivariate analyses of the two candidates, both socio-economic and health variables were significantly associated with voting patterns, with wealthier and healthier departments more likely to vote for Emmanuel Macron, and opposite departments more likely to vote for Marine Le Pen. Mortality (p = 0.03), severe chronic conditions (p = 0.014), and diabetes mellitus (p < 0.0001) were among the strongest predictors of voting pattern for Marine Le Pen. Sensitivity analyses did not substantially change those findings. Conclusions We found that areas associated with poorer health status were significantly more likely to vote for the far-right candidate at the French presidential election, even after adjustment on socioeconomic criteria.


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